Cheat-code, a collaborative to-do list

Hacker News

I've used all kinds of productivity apps but the best I've used (8 years and going) was a Google Sheet that I maintained with my friends where we would keep our to-do lists. Being able to see each others lists would make us actually complete those tasks in the face of peer pressure and shame. So we decided to make our sheet into a web app so that everyone can use it. It's basically a calendar where you keep a to-do list and your friends can view them. You can also comment on those tasks (it's great for keeping up with friends if you don't use Instagram like me) and get notifications. It's completely free, lmk what you think!

Visit product View on Hacker NewsAug 20, 2025

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Actual performance

2points

1comments

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, apps, tasks · Missing: mac, agents, macos

82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: apps, google · Missing: mobile apps, ios, personal

58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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